GET

/v1/schemas/voyage/embeddings/multimodalembeddings

Accept:

kind inputactivity embeddingshash 62b85d7d…extracted Aug 15, 2026version currentsource upstream spec ↗

field	recorded source
schema	Source linked above. upstream-spec Source trace `bcf93044ad36827296d6c899b51cb68e5dcad44467ab8b5a9ec012095bac8e6a` { "fetchedAt": 1786772015, "extractorVersion": "1", "verifiedAt": null }

Request body

5 properties · 2 required · 0 $defs

property	type	description	constraints
inputs*	any[]	A list of multimodal inputs to be vectorized.<br> <br> A single input in the list is a dictionary containing a single key `"content"`, whose value represents a sequence of text and images. <ul> <li> The value of <code>"content"</code> is a list of dictionaries…
model*	string	Name of the model. Currently, the only supported model is `voyage-multimodal-3`.
input_type	enum	Type of the input. Defaults to `null`. Other options: `query`, `document`. <ul> <li> When `input_type` is `null`, the embedding model directly converts the `inputs` into numerical vectors. For retrieval/search purposes, where a "query", which can be text or im…	null \| query \| document · default: null
truncation	boolean	Whether to truncate the inputs to fit within the context length. Defaults to `true`. <ul> <li> If `true`, an over-length input will be truncated to fit within the context length before being vectorized by the embedding model. If the truncation happens in the m…	default: true
output_encoding	enum	Format in which the embeddings are encoded. Defaults to `null`. <ul> <li> If `null`, the embeddings are represented as a list of floating-point numbers. </li> <li> If `base64`, the embeddings are represented as a Base64-encoded NumPy array of single-precision …	null \| base64 · default: null

Validate a payload

before you spend tokens

shell

$ curl -X POST https://modelschemas.com/v1/validate \
    -d '{"provider":"voyage","endpointId":"multimodalembeddings","payload":{…}}'
→ {"valid": false, "errors": [{"path": "#", "keyword": "required", …}]}